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NRI:INT: Ad-Hoc Collaborative Human-Robot Swarms

NRI:INT：特设协作人机群

基本信息

批准号：
1830471
负责人：
Hadas Kress Gazit
金额：
$ 149.06万
依托单位：
Cornell University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830471&HistoricalAwards=false
关键词：
NRI INT Ad Hoc Collaborative

项目摘要

This project addresses the challenge of creating ad-hoc collaborative teams (swarms) of robots and people, where the people are not robotics experts and are interacting with the robots to accomplish an ad-hoc task such as emergency evacuation. The project investigates what the robots should look like, how they should behave, and how they should interact with people without prior experience with robots, to make sure the overall task is accomplished. The scientific insights of this project can apply to different tasks such as crowd control and large scale search missions. Here the research is grounded in a series of room and building evacuation scenarios where robots work autonomously, provide information and guidance, and respond to people's requests and behaviors. This project will impact three graduate classes taught by the researchers, will support undergraduate and masters projects and the results will be incorporated into activities targeted at increasing the participation of groups traditionally underrepresented in engineering. This project advances knowledge in three subfields of robotics and especially at their intersection; swarm design, autonomy, and human-swarm interaction. The challenge includes development of hardware platforms that can traverse and modify their environment and permit safe human-robot interaction, while remaining inexpensive, robust, and low maintenance. Specifically, this will involve blimps to facilitate and provide broad situational awareness by projecting images on the ground, and ground robots with inflatable, interactive bladders. For autonomy, this project considers a top-down approach where individual robot control is synthesized from a high-level task. In addition, algorithms will be developed that enable robots to automatically modify their behavior and provide intuitive feedback based on interactions with humans, the humans' behaviors, and the observed environments. This project will contribute to the field of Human-Robot Interaction by designing and evaluating distributed interactions where the role of the human fluidly changes between being a leader providing instructions to the robots, a cooperative swarm member guided by the robots, an uncooperative member who acts in opposition to the swarm guidance, and a passive member who needs to be physically assisted. Evaluating the human-swarm behavior using established metrics in a variety of increasingly complex environments will provide unique insights into the opportunities and challenges of creating ad-hoc human-robot swarms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目解决了创建机器人和人员临时协作团队（群）的挑战，其中人员不是机器人专家，而是与机器人交互以完成紧急疏散等临时任务。该项目研究了机器人的外观、行为方式以及在没有机器人使用经验的情况下如何与人互动，以确保完成总体任务。该项目的科学见解可以应用于不同的任务，例如人群控制和大规模搜索任务。这项研究基于一系列房间和建筑物疏散场景，其中机器人自主工作，提供信息和指导，并响应人们的请求和行为。该项目将影响研究人员教授的三个研究生课程，将支持本科生和硕士项目，其结果将被纳入旨在增加传统上在工程领域代表性不足的群体参与的活动中。该项目推进了机器人技术三个子领域的知识，特别是它们的交叉领域；群体设计、自主性和人与群体的交互。挑战包括开发能够遍历和修改其环境并允许安全的人机交互的硬件平台，同时保持廉价、稳健和低维护成本。具体来说，这将涉及通过在地面上投射图像来促进和提供广泛态势感知的飞艇，以及带有可充气交互式气囊的地面机器人。对于自主性，该项目考虑了一种自上而下的方法，其中单个机器人控制是从高级任务综合而来的。此外，还将开发算法，使机器人能够自动修改其行为，并根据与人类的交互、人类的行为和观察到的环境提供直观的反馈。该项目将通过设计和评估分布式交互为人机交互领域做出贡献，其中人类的角色在向机器人提供指令的领导者、由机器人引导的合作群体成员、与群体引导相反的不合作成员以及需要物理协助的被动成员之间不断变化。在各种日益复杂的环境中使用既定指标评估人类群体行为，将为创建临时人类机器人群体的机遇和挑战提供独特的见解。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（11）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Exploring Human-Drone Collaboration Through Contact Improvisation

通过即兴接触探索人机协作

DOI：
10.1145/3568294.3580050
发表时间：
2023
期刊：
HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
影响因子：
0
作者：
Wilson-Small, Nialah Jenae;Pancoast, Louisa;Petersen, Kirstin;Azenkot, Shiri
通讯作者：
Azenkot, Shiri

Event-Based Signal Temporal Logic Tasks: Execution and Feedback in Complex Environments

基于事件的信号时序逻辑任务：复杂环境中的执行和反馈

DOI：
10.1109/lra.2022.3192625
发表时间：
2022
期刊：
IEEE Robotics and Automation Letters
影响因子：
5.2
作者：
Gundana, David;Kress-Gazit, Hadas
通讯作者：
Kress-Gazit, Hadas

Touchibo: Multimodal Texture-Changing Robotic Platform for Shared Human Experiences

Touchibo：用于共享人类体验的多模式纹理改变机器人平台

DOI：
发表时间：
2022
期刊：
UIST '22 Adjunct: Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology
影响因子：
0
作者：
Hu, Yuhan;Neto, Isabel;Ryu, Jin;Shtarbanov, Ali;Nicolau, Hugo;Paiva, Ana;Hoffman, Guy
通讯作者：
Hoffman, Guy

ShadowSense: Detecting Human Touch in a Social Robot Using Shadow Image Classification

ShadowSense：使用阴影图像分类检测社交机器人中的人体触摸